I have a structured retail dataset sitting in a single CSV file and I need it transformed into actionable insight. Your mission is to dive into the numbers, uncover the key trends and recurring patterns, and package everything so it is easy for our merchandising and marketing teams to digest. You are free to use the modern data-science toolkit you’re most comfortable with—Python (pandas, NumPy, seaborn / matplotlib), R, or even a SQL pipeline that feeds a visual layer—as long as the results are fully reproducible. What I expect: • A short, well-written insight report summarising the main patterns you detect (sales seasonality, product/category hotspots, customer behaviour shifts, etc.). • Clear visualisations that spotlight those findings. • The cleaned dataset plus the notebook or scripts you used, with comments so we can rerun everything in-house. If you notice any data quality issues while exploring, include a brief note on how you handled them. I’ll be available for quick clarifications throughout the project and can turn around feedback fast so you can keep moving. Let’s reveal what this retail data is really saying.